docstr: ivy.Array instance method variant of ivy.instance_norm. This method
  simply wraps the function, and so the docstring for ivy.instance_norm
  also applies to this method with minimal changes.
  
  Parameters
  ----------
  self
      Input array of shape default (N, *S, C), where N is the batch dimension,
      *S corresponds to any number of spatial dimensions and
       C corresponds to the channel dimension.
  mean
      Mean array of size C used for input's normalization.
  variance
      Variance array of size C used for input's normalization.
  offset
      An offset array of size C. If present, will be added
      to the normalized input.
  scale
      A scale array of size C. If present, the scale is
      applied to the normalized input.
  training
      If true, calculate and use the mean and variance of `x`. Otherwise, use the
      provided `mean` and `variance`.
  eps
      A small float number to avoid dividing by 0.
  momentum
       the value used for the running_mean and running_var computation.
        Default value is 0.1.
  data_format
      The ordering of the dimensions in the input, one of "NSC" or "NCS",
      where N is the batch dimension, S represents any number of spatial
      dimensions and C is the channel dimension. Default is "NSC".
  out
      optional output array, for writing the result to.
  
  Returns
  -------
  ret
       Tuple of array containing
        the normalized input, running mean, and running variance.
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code: def instance_norm(
      self: Union[ivy.NativeArray, ivy.Array],
      mean: Union[ivy.NativeArray, ivy.Array],
      variance: Union[ivy.NativeArray, ivy.Array],
      /,
      *,
      offset: Optional[Union[ivy.NativeArray, ivy.Array]] = None,
      scale: Optional[Union[ivy.NativeArray, ivy.Array]] = None,
      training: bool = False,
      eps: float = 1e-5,
      momentum: float = 1e-1,
      data_format: str = "NSC",
      out: Optional[Tuple[ivy.Array, ivy.Array, ivy.Array]] = None,
  ) -> Tuple[ivy.Array, ivy.Array, ivy.Array]:
      """ivy.Array instance method variant of ivy.instance_norm. This method
      simply wraps the function, and so the docstring for ivy.instance_norm
      also applies to this method with minimal changes.
  
      Parameters
      ----------
      self
          Input array of shape default (N, *S, C), where N is the batch dimension,
          *S corresponds to any number of spatial dimensions and
           C corresponds to the channel dimension.
      mean
          Mean array of size C used for input's normalization.
      variance
          Variance array of size C used for input's normalization.
      offset
          An offset array of size C. If present, will be added
          to the normalized input.
      scale
          A scale array of size C. If present, the scale is
          applied to the normalized input.
      training
          If true, calculate and use the mean and variance of `x`. Otherwise, use the
          provided `mean` and `variance`.
      eps
          A small float number to avoid dividing by 0.
      momentum
           the value used for the running_mean and running_var computation.
            Default value is 0.1.
      data_format
          The ordering of the dimensions in the input, one of "NSC" or "NCS",
          where N is the batch dimension, S represents any number of spatial
          dimensions and C is the channel dimension. Default is "NSC".
      out
          optional output array, for writing the result to.
  
      Returns
      -------
      ret
           Tuple of array containing
            the normalized input, running mean, and running variance.
      """
      return ivy.instance_norm(
          self._data,
          mean,
          variance,
          scale=scale,
          offset=offset,
          training=training,
          eps=eps,
          momentum=momentum,
          out=out,
          data_format=data_format,
      )
  
file_path: ivy/ivy/data_classes/array/experimental/norms.py
imports: import abc
  from typing import Optional, Union, Tuple
  import ivy
label_desc: Use image node_id 4 for calling the _ArrayWithNormsExperimental obj's underlying member method code with example usage: obj.instance_norm() and returns: ivy